Search results for: comprehensive feature extraction

Authors: Katarina Pogacnik, Ursa Zakrajsek, Nejc Sirk, Ziga Lampret

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Due to an increase in living standards along with global population growth and a trend of urbanization, municipalities and regions are faced with an ever rising energy demand. A challenge has arisen for cities around the world to modify the energy supply chain in order to reduce its consumption and CO₂ emissions. The aim of our work is the development of a computational-analytical platform for dynamic support in decision-making and the determination of economic and technical indicators of energy efficiency in a smart city, named Energy Atlas. Similar products in this field focuse on a narrower approach, whereas in order to achieve its aim, this platform encompasses a wider spectrum of beneficial and important information for energy planning on a local or regional scale. GIS based interactive maps provide an extensive database on the potential, use and supply of energy and renewable energy sources along with climate, transport and spatial data of the selected municipality. Beneficiaries of Energy atlas are local communities, companies, investors, contractors as well as residents. The Energy Atlas platform consists of three modules named E-Planning, E-Indicators and E-Cooperation. The E-Planning module is a comprehensive data service, which represents a support towards optimal decision-making and offers a sum of solutions and feasibility of measures and their effects in the area of efficient use of energy and renewable energy sources. The E-Indicators module identifies, collects and develops optimal data and key performance indicators and develops an analytical application service for dynamic support in managing a smart city in regards to energy use and sustainable environment. In order to support cooperation and direct involvement of citizens of the smart city, the E-cooperation is developed with the purpose of integrating the interdisciplinary and sociological aspects of energy end-users. Interaction of all the above-described modules contributes to regional development because it enables for a precise assessment of the current situation, strategic planning, detection of potential future difficulties and also the possibility of public involvement in decision-making. From the implementation of the technology in Slovenian municipalities of Ljubljana, Piran, and Novo mesto, there is evidence to suggest that the set goals are to be achieved to a great extent. Such thorough urban energy planning tool is viewed as an important piece of the puzzle towards achieving a low-carbon society, circular economy and therefore, sustainable society.

Keywords: circular economy, energy atlas, energy management, energy planning, low-carbon society

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Authors: Angela T. H. Kwan, Wenjun Liang, Jack Wellington, Mohammad Mofatteh, Thanh N. Nguyen, Pingzhong Fu, Juanmei Chen, Zile Yan, Weijuan Wu, Yongting Zhou, Shuiquan Yang, Sijie Zhou, Yimin Chen

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Background: Endovascular Therapy (EVT)—in the form of mechanical thrombectomy—following intravenous thrombolysis is the standard gold treatment for patients with acute ischemic stroke (AIS) due to large vessel occlusion (LVO). It is well established that an ASPECTS ≥ 7 is associated with an increased likelihood of positive post-EVT outcomes, as compared to an ASPECTS < 7. There is also prognostic utility in coupling posterior circulation ASPECTS (pc-ASPECTS) with magnetic resonance imaging for evaluating the post-EVT functional outcome. However, the value of pc-ASPECTS applied to CT must be explored further to determine its usefulness in predicting functional outcomes following EVT. Objective: In this study, we aimed to determine whether pc-ASPECTS on CT can predict post-EVT functional outcomes among patients with AIS due to LVO. Methods: A total of 247 consecutive patients aged 18 and over receiving EVT for LVO-related AIS were recruited into a prospective database. The data were retrospectively analyzed between March 2019 to February 2022 from two comprehensive tertiary care stroke centers: Foshan Sanshui District People’s Hospital and First People's Hospital of Foshan in China. Patient parameters included EVT within 24hrs of symptom onset, premorbid modified Rankin Scale (mRS) ≤ 2, presence of distal and terminal cerebral blood vessel occlusion, and subsequent 24–72-hour post-stroke onset CT scan. Univariate comparisons were performed using the Fisher exact test or χ2 test for categorical variables and the Mann–Whitney U test for continuous variables. A p-value of ≤ 0.05 was statistically significant. Results: A total of 247 patients met the inclusion criteria; however, 3 were excluded due to the absence of post-CTs and 8 for pre-EVT ASPECTS < 7. Overall, 236 individuals were examined: 196 anterior circulation ischemic strokes and 40 posterior strokes of basilar artery occlusion. We found that both baseline post- and pc-ASPECTS ≥ 7 serve as strong positive markers of favorable outcomes at 90 days post-EVT. Moreover, lower rates of inpatient mortality/hospice discharge, 90-day mortality, and 90-day poor outcome were observed. Moreover, patients in the post-ASPECTS ≥ 7 anterior circulation group had shorter door-to-recanalization time (DRT), puncture-to-recanalization time (PRT), and last known normal-to-puncture-time (LKNPT). Conclusion: Patients of anterior and posterior circulation ischemic strokes with baseline post- and pc-ASPECTS ≥ 7 may benefit from EVT.

Keywords: endovascular therapy, thrombectomy, large vessel occlusion, cerebral ischemic stroke, ASPECTS

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Authors: Jonathan Munyoro, Takawira Machimbidza, Stephen Mutula

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The study investigates the current status of Intellectual Property (IP) information services in Zimbabwe's university libraries. Specifically, the study assesses the current IP information services offered in Zimbabwe’s university libraries, identifies challenges to the development of comprehensive IP information services in Zimbabwe’s university libraries, and suggests solutions for the development of IP information services in Zimbabwe’s university libraries. The study is born out of a realisation that research on IP information services in university libraries has received little attention, especially in developing country contexts, despite the fact that there are calls for heightened participation of university libraries in IP information services. In Zimbabwe, the launch of the National Intellectual Property Policy and Implementation Strategy 2018-2022 and the introduction of the Education 5.0 concept are set to significantly change the IP landscape in the country. Education 5.0 places more emphasis on innovation and industrialisation (in addition to teaching, community service, and research), and has the potential to shift the focus and level of IP output produced in higher and tertiary education institutions beyond copyrights and more towards commercially exploited patents, utility models, and industrial designs. The growing importance of IP commercialisation in universities creates a need for appropriate IP information services to assist students, academics, researchers, administrators, start-ups, entrepreneurs, and inventors. The critical challenge for university libraries is to reposition themselves and remain relevant in the new trajectory. Designing specialised information services to support increased IP generation and commercialisation appears to be an opportunity for university libraries to stay relevant in the knowledge economy. However, IP information services in Zimbabwe’s universities appear to be incomplete and focused mostly on assisting with research publications and copyright-related activities. Research on the existing status of IP services in university libraries in Zimbabwe is therefore necessary to help identify gaps and provide solutions in order to stimulate the growth of new forms of such services. The study employed a quantitative approach. An online questionnaire was administered to 57 academic librarians from 15 university libraries. Findings show that the current focus of the surveyed institutions is on providing scientific research support services (15); disseminating/sharing university research output (14); and copyright activities (12). More specialised IP information services such as IP education and training, patent information services, IP consulting services, IP online service platforms, and web-based IP information services are largely unavailable in Zimbabwean university libraries. Results reveal that the underlying challenge in the development of IP information services in Zimbabwe's university libraries is insufficient IP knowledge among academic librarians, which is exacerbated by inadequate IP management frameworks in university institutions. The study proposes a framework for the entrenchment of IP information services in Zimbabwe's university libraries.

Keywords: academic libraries, information services, intellectual property, IP knowledge, university libraries, Zimbabwe

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Authors: Stefano Iannello, Massimiliano Materazzi

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Fluidized bed reactor technologies are one of the most valuable pathways for thermochemical conversions of biogenic fuels due to their good operating flexibility. Nevertheless, there are still issues related to the mixing and separation of heterogeneous phases during operation with highly volatile feedstocks, including biomass and waste. At high temperatures, the volatile content of the feedstock is released in the form of the so-called endogenous bubbles, which generally exert a “lift” effect on the particle itself by dragging it up to the bed surface. Such phenomenon leads to high release of volatile matter into the freeboard and limited mass and heat transfer with particles of the bed inventory. The aim of this work is to get a better understanding of the behaviour of a single reacting particle in a hot fluidized bed reactor during the devolatilization stage. The analysis has been undertaken at different fluidization regimes and temperatures to closely mirror the operating conditions of waste-to-energy processes. Beechwood and polypropylene particles were used to resemble the biomass and plastic fractions present in waste materials, respectively. The non-invasive X-ray technique was coupled to particle tracking algorithms to characterize the motion of a single feedstock particle during the devolatilization with high resolution. A high-energy X-ray beam passes through the vessel where absorption occurs, depending on the distribution and amount of solids and fluids along the beam path. A high-speed video camera is synchronised to the beam and provides frame-by-frame imaging of the flow patterns of fluids and solids within the fluidized bed up to 72 fps (frames per second). A comprehensive mathematical model has been developed in order to validate the experimental results. Beech wood and polypropylene particles have shown a very different dynamic behaviour during the pyrolysis stage. When the feedstock is fed from the bottom, the plastic material tends to spend more time within the bed than the biomass. This behaviour can be attributed to the presence of the endogenous bubbles, which drag effect is more pronounced during the devolatilization of biomass, resulting in a lower residence time of the particle within the bed. At the typical operating temperatures of thermochemical conversions, the synthetic polymer softens and melts, and the bed particles attach on its outer surface, generating a wet plastic-sand agglomerate. Consequently, this additional layer of sand may hinder the rapid evolution of volatiles in the form of endogenous bubbles, and therefore the establishment of a poor drag effect acting on the feedstock itself. Information about the mixing and segregation of solid feedstock is of prime importance for the design and development of more efficient industrial-scale operations.

Keywords: fluidized bed, pyrolysis, waste feedstock, X-ray

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Authors: Kim Katherine Castillo, Nelson John Datubatang, Terrence Phillip Dy, Norelie Hampac, Reichen Crismark Martinez, Nina Faith Pantinople, Jose Dante Santos II, Marchel Ann Santos, Sophia Abigail Santiago, Zyrill Xsar San Juan, Aira Mae Tagao, Crystal Kylla Viagedor

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The Work Immersion Program was implemented to help students gain abundant work-related experiences while on-site; additionally, the program aims to help students improve their competencies and interpersonal skills as they are given the option to join the workforce if they ever choose to do so after senior high school. The work immersion experience posed diverse challenges for students, spanning personal, financial, engagement, environmental, and equipment-related domains. These included the need for assistance in time management, transportation expenses, and procurement of materials. Furthermore, students faced difficulties in independent task completion and encountered suboptimal work environments. Addressing these multifaceted obstacles is crucial to optimize the educational outcomes of work immersion programs. In addition to the challenges, several other issues have been identified, including the absence of standardized work immersion programs across schools and industries, the challenges in securing appropriate work immersion placements, the necessity for enhanced monitoring and evaluation of program effectiveness, and the limited availability of field programs aligned with students' chosen courses. Furthermore, there is a lack of comprehensive information regarding the attitudes of Senior High School students toward work immersion programs within their respective schools. This study aims to investigate the attitudes of senior high school students at Nazareth School of National University towards work immersion programs, with a focus on identifying factors that influence their perception and participation, including collegiality and expectations. By exploring the students' attitudes, the research endeavors to enhance the school's work immersion programs and contribute to the overall educational experience of the students. This study addresses challenges related to work immersion programs, focusing on six subtopics: Work Immersion, Work Immersion in the Philippines, Students' Attitudes, Factors Affecting Students' Attitudes, Effectiveness of Work Immersion for Senior High School Students, and Students' Perception and Willingness to Participate. Using a descriptive research design, the study examines the attitudes of senior high school students at Nazareth School of National University in Manila. Data was collected from 100 students, representing different academic strands, through a 35-item researcher-made survey. Descriptive statistics, including measures of central tendency and variability, will be used to analyze the data using JASP, providing valuable insights into the students' attitudes toward work immersion.

Keywords: attitudes, challenges, educational outcomes, work immersion programs

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Authors: Ting-I Lin

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Purpose: This article explores the care experience of a 34-year-old female breast cancer patient who was admitted to the intensive care unit after undergoing a modified radical mastectomy. The patient discovered a lump in her right breast during a self-examination and, after mammography and ultrasound-guided biopsy, was diagnosed with a malignant tumor in the right breast. The tumor measured 1.5 x 1.4 x 2 cm, and the patient underwent a modified radical mastectomy. Postoperatively, she exhibited feelings of inferiority due to changes in her appearance. Method: During the care period, we engaged in conversations, observations, and active listening, using Gordon's Eleven Functional Health Patterns for a comprehensive assessment. In collaboration with the critical care team, a psychologist, and an oncology case manager, we conducted an interdisciplinary discussion and reached a consensus on key nursing issues. These included pain related to postoperative tumor excision and disturbed body image due to changes in appearance after surgery. Result: During the care period, a private space was provided to encourage the patient to express her feelings about her altered body image. Communication was conducted through active listening and a non-judgmental approach. The patient's anxiety level, as measured by the depression and anxiety scale, decreased from moderate to mild, and she was able to sleep for 6-8 hours at night. The oncology case manager was invited to provide education on breast reconstruction using breast models and videos to both the patient and her husband. This helped rebuild the patient's confidence. With the patient's consent, a support group was arranged where a peer with a similar experience shared her journey, offering emotional support and encouragement. This helped alleviate the psychological stress and shock caused by the cancer diagnosis. Additionally, pain management was achieved through adjusting the dosage of analgesics, administering Ultracet 37.5 mg/325 mg 1# Q6H PO, along with distraction techniques and acupressure therapy. These interventions helped the patient relax and alleviate discomfort, maintaining her pain score at a manageable level of 3, indicating mild pain. Conclusion: Disturbance in body image can cause significant psychological stress for patients. Through support group discussions, encouraging patients to express their feelings, and providing appropriate education on breast reconstruction and dressing techniques, the patient's self-concept was positively reinforced, and her emotions were stabilized. This led to renewed self-worth and confidence.

Keywords: breast cancer, modified radical mastectomy, acupressure therapy, Gordon's 11 functional health patterns

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Authors: Maciej Czarnecki

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Even though growth is one of the most important strategic objectives for many enterprises, we know relatively little about this phenomenon. This research contributes to broaden our knowledge of managerial consequences of growth. Scales for measuring organizational development and growing pains were developed. Conceptual model of connections among growth, organizational development, growing pains, selected development factors and financial performance were examined. The research process contained literature review, 20 interviews with managers, examination of 12 raters’ opinions, pilot research and 7 point Likert scale questionnaire research on 138 Polish enterprises employing 50-249 people which increased their employment at least by 50% within last three years. Factor analysis, Pearson product-moment correlation coefficient, student’s t-test and chi-squared test were used to develop scales. High Cronbach’s alpha coefficients were obtained. The verification of correlations among the constructs was carried out with factor correlations, multiple regressions and path analysis. When the enterprise grows, it is necessary to implement changes in its structure, management practices etc. (organizational development) to meet challenges of growing complexity. In this paper, organizational development was defined as internal changes aiming to improve the quality of existing or to introduce new elements in the areas of processes, organizational structure and culture, operational and management systems. Thus; H1: Growth has positive effects on organizational development. The main thesis of the research is that if organizational development does not catch up　with growing complexity of growing enterprise, growing pains will arise (lower work comfort, conflicts, lack of control etc.). They will exert a negative influence on the financial performance and may result in serious organizational crisis or even bankruptcy. Thus; H2: Growth has positive effects on growing pains, H3: Organizational development has negative effects on growing pains, H4: Growing pains have negative effects on financial performance, H5: Organizational development has positive effects on financial performance. Scholars considered long lists of factors having potential influence on organizational development. The development of comprehensive model taking into account all possible variables may be beyond the capacity of any researcher or even statistical software used. After literature review, it was decided to increase the level of abstraction and to include following constructs in the conceptual model: organizational learning (OL), positive organization (PO) and high performance factors (HPF). H1a/b/c: OL/PO/HPF has positive effect on organizational development, H2a/b/c: OL/PO/HPF has negative effect on growing pains. The results of hypothesis testing: H1: partly supported, H1a/b/c: supported/not supported/supported, H2: not supported, H2a/b/c: not supported/partly supported/not supported, H3: supported, H4: partly supported, H5: supported. The research seems to be of a great value for both scholars and practitioners. It proved that OL and HPO matter for organizational development. Scales for measuring organizational development and growing pains were developed. Its main finding, though, is that organizational development is a good way of improving financial performance.

Keywords: organizational development, growth, growing pains, financial performance

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Authors: Trevor Toy, Josef Langerman

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Around a quarter of the world’s data is generated by financial with an estimated 708.5 billion global non-cash transactions reached between 2018 and. And with Open Banking still a rapidly developing concept within the financial industry, there is an opportunity to create a secure mechanism for connecting its stakeholders to openly, legitimately and consensually share the data required to enable it. Integration and data sharing of anonymised transactional data are still operated in silos and centralised between the large corporate entities in the ecosystem that have the resources to do so. Smaller fintechs generating data and businesses looking to consume data are largely excluded from the process. Therefore there is a growing demand for accessible transactional data for analytical purposes and also to support the rapid global adoption of Open Banking. The following research has provided a solution framework that aims to provide a secure decentralised marketplace for 1.) data providers to list their transactional data, 2.) data consumers to find and access that data, and 3.) data subjects (the individuals making the transactions that generate the data) to manage and sell the data that relates to themselves. The platform also provides an integrated system for downstream transactional-related data from merchants, enriching the data product available to build a comprehensive view of a data subject’s spending habits. A robust and sustainable data market can be developed by providing a more accessible mechanism for data producers to monetise their data investments and encouraging data subjects to share their data through the same financial incentives. At the centre of the platform is the market mechanism that connects the data providers and their data subjects to the data consumers. This core component of the platform is developed on a decentralised blockchain contract with a market layer that manages transaction, user, pricing, payment, tagging, contract, control, and lineage features that pertain to the user interactions on the platform. One of the platform’s key features is enabling the participation and management of personal data by the individuals from whom the data is being generated. This framework developed a proof-of-concept on the Etheruem blockchain base where an individual can securely manage access to their own personal data and that individual’s identifiable relationship to the card-based transaction data provided by financial institutions. This gives data consumers access to a complete view of transactional spending behaviour in correlation to key demographic information. This platform solution can ultimately support the growth, prosperity, and development of economies, businesses, communities, and individuals by providing accessible and relevant transactional data for big data analytics and open banking.

Keywords: big data markets, open banking, blockchain, personal data management

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Authors: R. M. Kilonzo, S. Bedingfield, K. Smith, K. Hudgins Smith, K. Couper, R. Ratley, Z. Taylor, A. Engelman, M. Renne

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Introduction: The mental health needs of university students continue to evolve, necessitating a strategic approach to service delivery. The East Tennessee State University (ETSU) Counseling Center developed its inaugural Strategic Plan (2024-2028) to enhance student mental health services. The plan focuses on improving access, quality of care, and service visibility, aligning with the university’s mission to support academic success and student well-being. Aim: This strategic plan aims to establish a comprehensive framework for delivering high-quality, evidence-based mental health services to ETSU students, addressing current challenges, and anticipating future needs. Methods: The development of the strategic plan was a collaborative effort involving the Counseling Center’s leadership, staff, with technical support from Doctor of Public Health-community and behavioral health intern. Multiple workshops, online/offline reviews, and stakeholder consultations were held to ensure a robust and inclusive process. A SWOT analysis and stakeholder mapping were conducted to identify strengths, weaknesses, opportunities, and challenges. Key performance indicators (KPIs) were set to measure service utilization, satisfaction, and outcomes. Results: The plan resulted in four strategic priorities: service application, visibility/accessibility, safety and satisfaction, and training programs. Key objectives include expanding counseling services, improving service access through outreach, reducing stigma, and increasing peer support programs. The plan also focuses on continuous quality improvement through data-driven assessments and research initiatives. Immediate outcomes include expanded group therapy, enhanced staff training, and increased mental health literacy across campus. Conclusion and Recommendation: The strategic plan provides a roadmap for addressing the mental health needs of ETSU students, with a clear focus on accessibility, inclusivity, and evidence-based practices. Implementing the plan will strengthen the Counseling Center’s capacity to meet the diverse needs of the student population. To ensure sustainability, it is recommended that the center continuously assess student needs, foster partnerships with university and external stakeholders, and advocate for increased funding to expand services and staff capacity.

Keywords: strategic plan, university counseling center, mental health, students

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Authors: Shiau-Fang Chao, Yu-Chih Chen

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Owing to physical limitations and restrained lifestyle, older long-term care (LTC) residents are more likely to be affected by their environment than their community-dwelling counterparts. They also participate fewer activities and experience worse mental health than healthy older adults. This study adopts the ICF model to determine the extent to which the clustered patterns of LTC environment and activity participation are associated with older residents’ mental health. Method: Data were collected from a stratified equal probability sample of 634 older residents in 155 LTC institutions in Taiwan. Latent profile analysis (LPA) and latent class analysis (LCA) were conducted to explore the profiles for environment and activity participation. Multilevel modeling was performed to elucidate the relationships among environment profiles, activity profiles, and mental health. Results: LPA identified three mutually exclusive environment profiles (Low-, Moderate-, and High-Support Environment) based on the physical, social, and attitudinal environmental domains, consolidated from 12 environmental measures. LCA constructed two distinct activity profiles (Low- and High-Activity Participation) across seven activity domains (outdoor, volunteer-led leisure, spiritual, household chores, interpersonal exchange, social, and sedentary activity) that were factored from 20 activities. Compared to the Low-Support Environment class, older adults in the Moderate- and High-Support Environment classes had better mental health. Older residents in the Moderate- and High-Support Environment classes were more likely to be in the “High Activity” class, which in turn, exhibited better mental health. Conclusion: This study advances the current knowledge through rigorous methods and study design. The study findings lead to several conclusions. First, this study supports the use of ICF framework to institutionalized older individuals with functional limitations and demonstrates that both measures of environment and activity participation can be refined from multiple indicators. Second, environmental measures that encompass the physical, social, and attitudinal domains would provide a more comprehensive assessment on the place where an older individual embeds. Third, simply counting activities in which an older individual participates or considering a certain type of activity may not capture his or her way of life. Practitioners should not only focus on group or leisure activities within the institutions; rather, more efforts should be made to consider residents’ preferences for everyday life and support their remaining ability by encouraging continuous participation in activities they still willing and capable to perform. Fourth, environment and activity participation are modifiable factors which have greater potential to strengthen older LTC residents’ mental health, and activity participation should be considered in the link between environment and mental health. A combination of enhanced physical, social, and attitudinal environments, and continual engagement in various activities may optimize older LTC residents’ mental health.

Keywords: activity, environment, mental health, older LTC residents

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Authors: Hongmei Wang, Ziyun Xiang, Ying liu, Li Yu, Dongsheng Yue

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Intro: The COVID-19 (Corona Virus Disease 2019) has greatly changed the global economic, political and financial ecology. The mutation of the coronavirus in the UK in December 2020 has brought new panic to the world. Deep learning was performed on Chest Computed tomography (CT) of COVID-19 and Influenza and describes their characteristics. The predominant features of COVID-19 pneumonia was ground-glass opacification, followed by consolidation. Lesion density: most lesions appear as ground-glass shadows, and some lesions coexist with solid lesions. Lesion distribution: the focus is mainly on the dorsal side of the periphery of the lung, with the lower lobe of the lungs as the focus, and it is often close to the pleura. Other features it has are grid-like shadows in ground glass lesions, thickening signs of diseased vessels, air bronchi signs and halo signs. The severe disease involves whole bilateral lungs, showing white lung signs, air bronchograms can be seen, and there can be a small amount of pleural effusion in the bilateral chest cavity. At the same time, this year's flu season could be near its peak after surging throughout the United States for months. Chest CT for Influenza infection is characterized by focal ground glass shadows in the lungs, with or without patchy consolidation, and bronchiole air bronchograms are visible in the concentration. There are patchy ground-glass shadows, consolidation, air bronchus signs, mosaic lung perfusion, etc. The lesions are mostly fused, which is prominent near the hilar and two lungs. Grid-like shadows and small patchy ground-glass shadows are visible. Deep neural networks have great potential in image analysis and diagnosis that traditional machine learning algorithms do not. Method: Aiming at the two major infectious diseases COVID-19 and influenza, which are currently circulating in the world, the chest CT of patients with two infectious diseases is classified and diagnosed using deep learning algorithms. The residual network is proposed to solve the problem of network degradation when there are too many hidden layers in a deep neural network (DNN). The proposed deep residual system (ResNet) is a milestone in the history of the Convolutional neural network (CNN) images, which solves the problem of difficult training of deep CNN models. Many visual tasks can get excellent results through fine-tuning ResNet. The pre-trained convolutional neural network ResNet is introduced as a feature extractor, eliminating the need to design complex models and time-consuming training. Fastai is based on Pytorch, packaging best practices for in-depth learning strategies, and finding the best way to handle diagnoses issues. Based on the one-cycle approach of the Fastai algorithm, the classification diagnosis of lung CT for two infectious diseases is realized, and a higher recognition rate is obtained. Results: A deep learning model was developed to efficiently identify the differences between COVID-19 and influenza using chest CT.

Keywords: COVID-19, Fastai, influenza, transfer network

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Authors: Sally Naji, Julie Gwilliam

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Climate change remains a challenging matter for the human and the built environment in the 21st century, where the need to consider adaptation to climate change in the development process is paramount. However, there remains a lack of information regarding how we should prepare responses to this issue, such as through developing organized and sophisticated tools enabling the adaptation process. This study aims to build a systematic framework approach to investigate the potentials that Neighborhood Sustainability Assessment tools (NSA) might offer in enabling both the analysis of the emerging adaptive capacity to climate change. The analysis of the framework presented in this paper aims to discuss this issue in three main phases. The first part attempts to link sustainability and climate change, in the context of adaptive capacity. It is argued that in deciding to promote sustainability in the context of climate change, both the resilience and vulnerability processes become central. However, there is still a gap in the current literature regarding how the sustainable development process can respond to climate change. As well as how the resilience of practical strategies might be evaluated. It is suggested that the integration of the sustainability assessment processes with both the resilience thinking process, and vulnerability might provide important components for addressing the adaptive capacity to climate change. A critical review of existing literature is presented illustrating the current lack of work in this field, integrating these three concepts in the context of addressing the adaptive capacity to climate change. The second part aims to identify the most appropriate scale at which to address the built environment for the climate change adaptation. It is suggested that the neighborhood scale can be considered as more suitable than either the building or urban scales. It then presents the example of NSAs, and discusses the need to explore their potential role in promoting the adaptive capacity to climate change. The third part of the framework presents a comparison among three example NSAs, BREEAM Communities, LEED-ND, and CASBEE-UD. These three tools have been selected as the most developed and comprehensive assessment tools that are currently available for the neighborhood scale. This study concludes that NSAs are likely to present the basis for an organized framework to address the practical process for analyzing and yet promoting Adaptive Capacity to Climate Change. It is further argued that vulnerability (exposure & sensitivity) and resilience (Interdependence & Recovery) form essential aspects to be addressed in the future assessment of NSA’s capability to adapt to both short and long term climate change impacts. Finally, it is acknowledged that further work is now required to understand impact assessment in terms of the range of physical sectors (Water, Energy, Transportation, Building, Land Use and Ecosystems), Actor and stakeholder engagement as well as a detailed evaluation of the NSA indicators, together with a barriers diagnosis process.

Keywords: adaptive capacity, climate change, NSA tools, resilience, sustainability

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Authors: Shankaran Sitarama

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New Product Development involves team members coming together and working in teams to come up with innovative solutions to problems, resulting in new products. Thus, a core attribute of a successful NPD team is their creativity and innovation. They need to be creative as a group, generating a breadth of ideas and innovative solutions that solve or address the problem they are targeting and meet the user’s needs. They also need to be very efficient in their teamwork as they work through the various stages of the development of these ideas, resulting in a POC (proof-of-concept) implementation or a prototype of the product. There are two distinctive traits that the teams need to have, one is ideational creativity, and the other is effective and efficient teamworking. There are multiple types of tensions that each of these traits cause in the teams, and these tensions reflect in the team dynamics. Ideational conflicts arising out of debates and deliberations increase the collective knowledge and affect the team creativity positively. However, the same trait of challenging each other’s viewpoints might lead the team members to be disruptive, resulting in interpersonal tensions, which in turn lead to less than efficient teamwork. Teams that foster and effectively manage these creative tensions are successful, and teams that are not able to manage these tensions show poor team performance. In this paper, it explore these tensions as they result in the team communication social network and propose a Creative Tension Balance index along the lines of Degree of Balance in social networks that has the potential to highlight the successful (and unsuccessful) NPD teams. Team communication reflects the team dynamics among team members and is the data set for analysis. The emails between the members of the NPD teams are processed through a semantic analysis algorithm (LSA) to analyze the content of communication and a semantic similarity analysis to arrive at a social network graph that depicts the communication amongst team members based on the content of communication. This social network is subjected to traditional social network analysis methods to arrive at some established metrics and structural balance analysis metrics. Traditional structural balance is extended to include team interaction pattern metrics to arrive at a creative tension balance metric that effectively captures the creative tensions and tension balance in teams. This CTB (Creative Tension Balance) metric truly captures the signatures of successful and unsuccessful (dissonant) NPD teams. The dataset for this research study includes 23 NPD teams spread out over multiple semesters and computes this CTB metric and uses it to identify the most successful and unsuccessful teams by classifying these teams into low, high and medium performing teams. The results are correlated to the team reflections (for team dynamics and interaction patterns), the team self-evaluation feedback surveys (for teamwork metrics) and team performance through a comprehensive team grade (for high and low performing team signatures).

Keywords: team dynamics, social network analysis, new product development teamwork, structural balance, NPD teams

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Authors: V. Mantey, N. Findlay, I. Maddox

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The quality and quantity of global satellite data have been increasing exponentially in recent years as spaceborne systems become more affordable and the sensors themselves become more sophisticated. This is a valuable resource for many applications, including disaster management and relief. However, while more information can be valuable, the volume of data available is impossible to manually examine. Therefore, the question becomes how to extract as much information as possible from the data with limited manpower. Buildings are a key feature of interest in satellite imagery with applications including telecommunications, population models, and disaster relief. Machine learning tools are fast becoming one of the key resources to solve this problem, and models have been developed to detect buildings in optical satellite imagery. However, by and large, most models focus on affluent regions where buildings are generally larger and constructed further apart. This work is focused on the more difficult problem of detection in populated regions. The primary challenge with detecting small buildings in densely populated regions is both the spatial and spectral resolution of the optical sensor. Densely packed buildings with similar construction materials will be difficult to separate due to a similarity in color and because the physical separation between structures is either non-existent or smaller than the spatial resolution. This study finds that training models until they are overfitting the input sample can perform better in these areas than a more robust, generalized model. An overfitted model takes less time to fine-tune from a generalized pre-trained model and requires fewer input data. The model developed for this study has also been fine-tuned using existing, open-source, building vector datasets. This is particularly valuable in the context of disaster relief, where information is required in a very short time span. Leveraging existing datasets means that little to no manpower or time is required to collect data in the region of interest. The training period itself is also shorter for smaller datasets. Requiring less data means that only a few quality areas are necessary, and so any weaknesses or underpopulated regions in the data can be skipped over in favor of areas with higher quality vectors. In this study, a landcover classification model was developed in conjunction with the building detection tool to provide a secondary source to quality check the detected buildings. This has greatly reduced the false positive rate. The proposed methodologies have been implemented and integrated into a configurable production environment and have been employed for a number of large-scale commercial projects, including continent-wide DEM production, where the extracted building footprints are being used to enhance digital elevation models. Overfitted machine learning models are often considered too specific to have any predictive capacity. However, this study demonstrates that, in cases where input data is scarce, overfitted models can be judiciously applied to solve time-sensitive problems.

Keywords: building detection, disaster relief, mask-RCNN, satellite mapping

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Authors: Abhijit Trailokya

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Background: Cardiovascular diseases (CVD’s) are the major cause of morbidity and mortality in both developed and developing countries. Many clinical trials have demonstrated that low-density lipoprotein cholesterol (LDL-C) lowering, reduces the incidence of coronary and cerebrovascular events across a broad spectrum of patients at risk. Guidelines for the management of patients at risk have been established in Europe and North America. The guidelines have advocated progressively lower LDL-C targets and more aggressive use of statin therapy. In Indian patients, comprehensive data on dyslipidemia management and its treatment outcomes are inadequate. There is lack of information on existing treatment patterns, the patient’s profile being treated, and factors that determine treatment success or failure in achieving desired goals. Purpose: The present study was planned to determine the lipid control status in high-risk dyslipidemic patients treated with lipid-lowering therapy in India. Methods: This cross-sectional, non-interventional, single visit program was conducted across 483 sites in India where male and female patients with high-risk dyslipidemia aged 18 to 65 years who had visited for a routine health check-up to their respective physician at hospital or a healthcare center. Percentage of high-risk dyslipidemic patients achieving adequate LDL-C level (< 70 mg/dL) on lipid-lowering therapy and the association of lipid parameters with patient characteristics, comorbid conditions, and lipid lowering drugs were analysed. Results: 3089 patients were enrolled in the study; of which 64% were males. LDL-C data was available for 95.2% of the patients; only 7.7% of these patients achieved LDL-C levels < 70 mg/dL on lipid-lowering therapy, which may be due to inability to follow therapeutic plans, poor compliance, or inadequate counselling by physician. The physician’s lack of awareness about recent treatment guidelines also might contribute to patients’ poor adherence, not explaining adequately the benefit and risks of a medication, not giving consideration to the patient’s life style and the cost of medication. Statin was the most commonly used anti-dyslipidemic drug across population. The higher proportion of patients had the comorbid condition of CVD and diabetes mellitus across all dyslipidemic patients. Conclusion: As per the European Society of Cardiology guidelines the ideal LDL-C levels in high risk dyslipidemic patients should be less than 70%. In the present study, 7.7% of the patients achieved LDL-C levels < 70 mg/dL on lipid lowering therapy which is very less. Most of high risk dyslipidemic patients in India are on suboptimal dosage of statin. So more aggressive and high dosage statin therapy may be required to achieve target LDLC levels in high risk Indian dyslipidemic patients.

Keywords: cardiovascular disease, diabetes mellitus, dyslipidemia, LDL-C, lipid lowering drug, statins

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Authors: Hwang Ho Kim, Do Gyun Kim, Jin Young Choi, Sang Chul Park

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Since tire production process is very complicated, company-wide management of it is very difficult, necessitating considerable amounts of capital and labors. Thus, productivity should be enhanced and maintained competitive by developing and applying effective production plans. Among major processes for tire manufacturing, consisting of mixing component preparation, building and curing, the mixing process is an essential and important step because the main component of tire, called compound, is formed at this step. Compound as a rubber synthesis with various characteristics plays its own role required for a tire as a finished product. Meanwhile, scheduling tire mixing process is similar to flexible job shop scheduling problem (FJSSP) because various kinds of compounds have their unique orders of operations, and a set of alternative machines can be used to process each operation. In addition, setup time required for different operations may differ due to alteration of additives. In other words, each operation of mixing processes requires different setup time depending on the previous one, and this kind of feature, called sequence dependent setup time (SDST), is a very important issue in traditional scheduling problems such as flexible job shop scheduling problems. However, despite of its importance, there exist few research works dealing with the tire mixing process. Thus, in this paper, we consider the scheduling problem for tire mixing process and suggest an efficient particle swarm optimization (PSO) algorithm to minimize the makespan for completing all the required jobs belonging to the process. Specifically, we design a particle encoding scheme for the considered scheduling problem, including a processing sequence for compounds and machine allocation information for each job operation, and a method for generating a tire mixing schedule from a given particle. At each iteration, the coordination and velocity of particles are updated, and the current solution is compared with new solution. This procedure is repeated until a stopping condition is satisfied. The performance of the proposed algorithm is validated through a numerical experiment by using some small-sized problem instances expressing the tire mixing process. Furthermore, we compare the solution of the proposed algorithm with it obtained by solving a mixed integer linear programming (MILP) model developed in previous research work. As for performance measure, we define an error rate which can evaluate the difference between two solutions. As a result, we show that PSO algorithm proposed in this paper outperforms MILP model with respect to the effectiveness and efficiency. As the direction for future work, we plan to consider scheduling problems in other processes such as building, curing. We can also extend our current work by considering other performance measures such as weighted makespan or processing times affected by aging or learning effects.

Keywords: compound, error rate, flexible job shop scheduling problem, makespan, particle encoding scheme, particle swarm optimization, sequence dependent setup time, tire mixing process

Procedia PDF Downloads 265

Authors: Shilpi Bora, Abhirup Chatterjee, Debkumar Chakrabarti

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Organizations of all the sectors around the world are increasingly revisiting their workplace strategies with due concern for women working therein. Limited office space and rigid work arrangements contribute to lesser job satisfaction and greater work impoundments for any organization. Flexible workspace strategies are indispensable to accommodate the progressive rise of modular workstations and involvement of women. Today’s generation of employees deserves malleable office environments with employee-friendly job conditions and strategies. The workplace nowadays stands on rapid organizational changes in progressive and flexible work culture. Occupational well-being practices need to keep pace with the rapid changes in office-based work. Working at the office (workspace) with awkward postures or for long periods can cause pain, discomfort, and injury. The world is stirring towards the era of globalization and progress. The 4000 women police personnel constitute less than one per cent of the total police strength of India. Lots of innovative fields are growing fast, and it is important that we should accommodate women in those arenas. The timeworn trends should be set apart to set out for fresh opportunities and possibilities of development and success through more involvement of women in the workplace. The notion of women policing is gaining position throughout the world, and various countries are putting solemn efforts to mainstream women in policing. As the role of women policing in a society is budding, and thus it is also notable that the accessibility of women at general police stations should be considered. Accordingly, the impact of workspace at police station on the employee productivity has been widely deliberated as a crucial contributor to employee satisfaction leading to better functional motivation. Thus the present research aimed to look into the office workstation design of police station with reference to womanhood specific issues to uplift occupational wellbeing of the policewomen. Personal interview and individual responses collected through administering to a subjective assessment questionnaire on thirty women police as well as to have their views on these issues by purposive non-probability sampling of women police personnel of different ranks posted in Guwahati, Assam, India. Scrutiny of the collected data revealed that office design has a substantial impact on the policewomen job satisfaction in the police station. In this study, the workspace was designed in such a way that the set of factors would impact on the individual to ensure increased productivity. Office design such as furniture, noise, temperature, lighting and spatial arrangement were considered. The primary feature which affected the productivity of policewomen was the furniture used in the workspace, which was found to disturb the everyday and overall productivity of policewomen. Therefore, it was recommended to have proper and adequate ergonomics design intervention to improve the office design for better performance. This type of study is today’s need-of-the-hour to empower women and facilitate their inner talent to come up in service of the nation. The office workspace design also finds critical importance at several other occupations also – where office workstation needs further improvement.

Keywords: office workspace design, policewomen, womanhood concerns at workspace, occupational wellbeing

Procedia PDF Downloads 225

Authors: S. Srinivas Rao, Pallavi Chitnis, Himanshu Prajapati

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The green building movement in India commenced in 2003. Since then, more than 4,300 projects have adopted green building concepts. For last 15 years, the green building movement has grown strong across the country and has resulted in immense tangible and intangible benefits to the stakeholders. Several success stories have demonstrated the tangible benefit experienced in green buildings. However, extensive data interpretation and qualitative analysis are required to report the intangible benefits in green buildings. The emphasis is now shifting to the concept of people-centric design and productivity, health and wellbeing of occupants are gaining importance. This research was part of World Green Building Council’s initiative on 'Better Places for People' which aims to create a world where buildings support healthier and happier lives. The overarching objective of this study was to understand the perception of users living and working in green buildings. The study was conducted in twenty-five IGBC certified green buildings across India, and a comprehensive questionnaire was designed to capture occupant’s perception and experience in the built environment. The entire research focussed on the eight attributes of healthy buildings. The factors considered for the study include thermal comfort, visual comfort, acoustic comfort, ergonomics, greenery, fitness, green transit and sanitation and hygiene. The occupant’s perception and experience were analysed to understand their satisfaction level. The macro level findings of the study indicate that green buildings have addressed attributes of healthy buildings to a larger extent. Few important findings of the study focussed on the parameters such as visual comfort, fitness, greenery, etc. The study indicated that occupants give tremendous importance to the attributes such as visual comfort, daylight, fitness, greenery, etc. 89% occupants were comfortable with the visual environment, on account of various lighting element incorporated as part of the design. Tremendous importance to fitness related activities is highlighted by the study. 84% occupants had actively utilised sports and meditation facilities provided in their facility. Further, 88% occupants had access to the ample greenery and felt connected to the natural biodiversity. This study aims to focus on the immense advantages gained by users occupying green buildings. This will empower green building movement to achieve new avenues to design and construct healthy buildings. The study will also support towards implementing human-centric measures and in turn, will go a long way in addressing people welfare and wellbeing in the built environment.

Keywords: health and wellbeing, green buildings, Indian green building council, occupant’s satisfaction

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Authors: Mohsen Hababalahi, Morteza Bastami

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Buried pipeline damage correlations are critical part of loss estimation procedures applied to lifelines for future earthquakes. The vulnerability of buried pipelines against earthquake and liquefaction has been observed during some of previous earthquakes and there are a lot of comprehensive reports about this event. One of the main reasons for impairment of buried pipelines during earthquake is liquefaction. Necessary conditions for this phenomenon are loose sandy soil, saturation of soil layer and earthquake intensity. Because of this fact that pipelines structure are very different from other structures (being long and having light mass) by paying attention to the results of previous earthquakes and compare them with other structures, it is obvious that the danger of liquefaction for buried pipelines is not high risked, unless effective parameters like earthquake intensity and non-dense soil and other factors be high. Recent liquefaction researches for buried pipeline include experimental and theoretical ones as well as damage investigations during actual earthquakes. The damage investigations have revealed that a damage ratio of pipelines (Number/km ) has much larger values in liquefied grounds compared with one in shaking grounds without liquefaction according to damage statistics during past severe earthquakes, and that damages of joints and pipelines connected with manholes were remarkable. The purpose of this research is numerical study of buried pipelines under the effect of liquefaction by case study of the 2013 Dashti (Iran) earthquake. Water supply and electrical distribution systems of this township interrupted during earthquake and water transmission pipelines were damaged severely due to occurrence of liquefaction. The model consists of a polyethylene pipeline with 100 meters length and 0.8 meter diameter which is covered by light sandy soil and the depth of burial is 2.5 meters from surface. Since finite element method is used relatively successfully in order to solve geotechnical problems, we used this method for numerical analysis. For evaluating this case, some information like geotechnical information, classification of earthquakes levels, determining the effective parameters in probability of liquefaction, three dimensional numerical finite element modeling of interaction between soil and pipelines are necessary. The results of this study on buried pipelines indicate that the effect of liquefaction is function of pipe diameter, type of soil, and peak ground acceleration. There is a clear increase in percentage of damage with increasing the liquefaction severity. The results indicate that although in this form of the analysis, the damage is always associated to a certain pipe material, but the nominally defined “failures” include by failures of particular components (joints, connections, fire hydrant details, crossovers, laterals) rather than material failures. At the end, there are some retrofit suggestions in order to decrease the risk of liquefaction on buried pipelines.

Keywords: liquefaction, buried pipelines, lifelines, earthquake, finite element method

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Authors: Mariia Karizhenskaia, Tanvi Nandani, Ali Tafazoli Moghadam

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Hospice palliative care (HPC) is one of the most complicated philosophies of care in which physical, social/cultural, and spiritual aspects of human life are intermingled with an undeniably significant role in every aspect. Among these dimensions of care, culture possesses an outstanding position in the process and goal determination of HPC. This study shows the importance of cultural elements in the establishment of effective and optimized structures of HPC in the Canadian healthcare environment. Our systematic search included Medline, Google Scholar, and St. Lawrence College Library, considering original, peer-reviewed research papers published from 1998 to 2023 to identify recent national literature connecting culture and palliative care delivery. The most frequently presented feature among the articles is the role of culture in the efficiency of the HPC. It has been shown frequently that including the culturespecific parameters of each nation in this system of care is vital for its success. On the other hand, ignorance about the exclusive cultural trends in a specific location has been accompanied by significant failure rates. Accordingly, implementing a culture-wise adaptable approach is mandatory for multicultural societies. The following outcome of research studies in this field underscores the importance of culture-oriented education for healthcare staff. Thus, all the practitioners involved in HPC will recognize the importance of traditions, religions, and social habits for processing the care requirements. Cultural competency training is a telling sample of the establishment of this strategy in health care that has come to the aid of HPC in recent years. Another complexity of the culturized HPC nowadays is the long-standing issue of racialization. Systematic and subconscious deprivation of minorities has always been an adversity of advanced levels of care. The last part of the constellation of our research outcomes is comprised of the ethical considerations of culturally driven HPC. This part is the most sophisticated aspect of our topic because almost all the analyses, arguments, and justifications are subjective. While there was no standard measure for ethical elements in clinical studies with palliative interventions, many research teams endorsed applying ethical principles for all the involved patients. Notably, interpretations and projections of ethics differ in varying cultural backgrounds. Therefore, healthcare providers should always be aware of the most respectable methodologies of HPC on a case-by-case basis. Cultural training programs have been utilized as one of the main tactics to improve the ability of healthcare providers to address the cultural needs and preferences of diverse patients and families. In this way, most of the involved health care practitioners will be equipped with cultural competence. Considerations for ethical and racial specifications of the clients of this service will boost the effectiveness and fruitfulness of the HPC. Canadian society is a colorful compilation of multiple nationalities; accordingly, healthcare clients are diverse, and this divergence is also translated into HPC patients. This fact justifies the importance of studying all the cultural aspects of HPC to provide optimal care on this enormous land.

Keywords: cultural competence, end-of-life care, hospice, palliative care

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Authors: Ammar Alali, Mahmoud Abughaban

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Cost reduction and drilling optimization is the goal of many drilling operators. Historically, stuck pipe incidents were a major segment of non-productive time (NPT) associated costs. Traditionally, stuck pipe problems are part of the operations and solved post-sticking. However, the real key to savings and success is in predicting the stuck pipe incidents and avoiding the conditions leading to its occurrences. Previous attempts in stuck-pipe predictions have neglected the local geology of the problem. The proposed predictive tool utilizes geophysical data processing techniques and Machine Learning (ML) algorithms to predict drilling activities events in real-time using surface drilling data with minimum computational power. The method combines two types of analysis: (1) real-time prediction, and (2) cause analysis. Real-time prediction aggregates the input data, including historical drilling surface data, geological formation tops, and petrophysical data, from wells within the same field. The input data are then flattened per the geological formation and stacked per stuck-pipe incidents. The algorithm uses two physical methods (stacking and flattening) to filter any noise in the signature and create a robust pre-determined pilot that adheres to the local geology. Once the drilling operation starts, the Wellsite Information Transfer Standard Markup Language (WITSML) live surface data are fed into a matrix and aggregated in a similar frequency as the pre-determined signature. Then, the matrix is correlated with the pre-determined stuck-pipe signature for this field, in real-time. The correlation used is a machine learning Correlation-based Feature Selection (CFS) algorithm, which selects relevant features from the class and identifying redundant features. The correlation output is interpreted as a probability curve of stuck pipe incidents prediction in real-time. Once this probability passes a fixed-threshold defined by the user, the other component, cause analysis, alerts the user of the expected incident based on set pre-determined signatures. A set of recommendations will be provided to reduce the associated risk. The validation process involved feeding of historical drilling data as live-stream, mimicking actual drilling conditions, of an onshore oil field. Pre-determined signatures were created for three problematic geological formations in this field prior. Three wells were processed as case studies, and the stuck-pipe incidents were predicted successfully, with an accuracy of 76%. This accuracy of detection could have resulted in around 50% reduction in NPT, equivalent to 9% cost saving in comparison with offset wells. The prediction of stuck pipe problem requires a method to capture geological, geophysical and drilling data, and recognize the indicators of this issue at a field and geological formation level. This paper illustrates the efficiency and the robustness of the proposed cross-disciplinary approach in its ability to produce such signatures and predicting this NPT event.

Keywords: drilling optimization, hazard prediction, machine learning, stuck pipe

Procedia PDF Downloads 226

Authors: Adhimoolam Saravana Kumar, K. N. Govindarajan, B. Devanand, R. Rajakumar

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The quality of Computed Tomography (CT) procedures has improved in recent years due to technological developments and increased diagnostic ability of CT scanners. Due to the fact that CT doses are the peak among diagnostic radiology practices, it is of great significance to be aware of patient’s CT radiation dose whenever a CT examination is preferred. CT radiation dose delivered to patients in the form of volume CT dose index (CTDIvol) values, is displayed on scanner monitors at the end of each examination and it is an important fact to assure that this information is accurate. The objective of this study was to estimate the CTDIvol values for great number of patients during the most frequent CT examinations, to study the comparison between CT dose monitor values and measured ones, as well as to highlight the fluctuation of CTDIvol values for the same CT examination at different centres and scanner models. The output CT dose indices measurements were carried out on single and multislice scanners for available kV, 5 mm slice thickness, 100 mA and FOV combination used. The 100 CT scanners were involved in this study. Data with regard to 15,000 examinations in patients, who underwent routine head, chest and abdomen CT were collected using a questionnaire sent to a large number of hospitals. Out of the 15,000 examinations, 5000 were head CT examinations, 5000 were chest CT examinations and 5000 were abdominal CT examinations. Comprehensive quality assurance (QA) was performed for all the machines involved in this work. Followed by QA, CT phantom dose measurements were carried out in South India using actual scanning parameters used clinically by the hospitals. From this study, we have measured the mean divergence between the measured and displayed CTDIvol values were 5.2, 8.4, and -5.7 for selected head, chest and abdomen procedures for protocols as mentioned above, respectively. Thus, this investigation revealed an observable change in CT practices, with a much wider range of studies being performed currently in South India. This reflects the improved capacity of CT scanners to scan longer scan lengths and at finer resolutions as permitted by helical and multislice technology. Also, some of the CT scanners have used smaller slice thickness for routine CT procedures to achieve better resolution and image quality. It leads to an increase in the patient radiation dose as well as the measured CTDIv, so it is suggested that such CT scanners should select appropriate slice thickness and scanning parameters in order to reduce the patient dose. If these routine scan parameters for head, chest and abdomen procedures are optimized than the dose indices would be optimal and lead to the lowering of the CT doses. In South Indian region all the CT machines were routinely tested for QA once in a year as per AERB requirements.

Keywords: CT dose index, weighted CTDI, volumetric CTDI, radiation dose

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Authors: Mohammadreza Bakhtiari, Mehrdad Maghsoudi, Hamidreza Bakhtiari

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This study investigates consumer behavior in the notebook computer market by integrating social media sentiment analysis with expert evaluations. The rapid evolution of the notebook industry has intensified competition among manufacturers, necessitating a deeper understanding of consumer priorities. Social media platforms, particularly Twitter, have become valuable sources for capturing real-time user feedback. In this research, sentiment analysis was performed on Twitter data gathered in the last two years, focusing on seven major notebook brands. The PyABSA framework was utilized to extract sentiments associated with various notebook components, including performance, design, battery life, and price. Expert evaluations, conducted using fuzzy logic, were incorporated to assess the impact of these sentiments on purchase behavior. To provide actionable insights, the TOPSIS method was employed to prioritize notebook features based on a combination of consumer sentiments and expert opinions. The findings consistently highlight price, display quality, and core performance components, such as RAM and CPU, as top priorities across brands. However, lower-priority features, such as webcams and cooling fans, present opportunities for manufacturers to innovate and differentiate their products. The analysis also reveals subtle but significant brand-specific variations, offering targeted insights for marketing and product development strategies. For example, Lenovo's strong performance in display quality points to a competitive edge, while Microsoft's lower ranking in battery life indicates a potential area for R&D investment. This hybrid methodology demonstrates the value of combining big data analytics with expert evaluations, offering a comprehensive framework for understanding consumer behavior in the notebook market. The study emphasizes the importance of aligning product development and marketing strategies with evolving consumer preferences, ensuring competitiveness in a dynamic market. It also underscores the potential for innovation in seemingly less important features, providing companies with opportunities to create unique selling points. By bridging the gap between consumer expectations and product offerings, this research equips manufacturers with the tools needed to remain agile in responding to market trends and enhancing customer satisfaction.

Keywords: consumer behavior, customer preferences, laptop industry, notebook computers, social media analytics, TOPSIS

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Authors: M. Amo, A. Alvaro, A. Astudillo, R. Mc Culloch, J. C. del Castillo, M. Gómez, J. M. Martín

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Polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) of course comprise a range of highly toxic compounds that may exist as particulates within the air or accumulate within water supplies, soil, or vegetation. They may be created either ubiquitously or naturally within the environment as a product of forest fires or volcanic eruptions. It is only since the industrial revolution, however, that it has become necessary to closely monitor their generation as a byproduct of manufacturing/combustion processes, in an effort to mitigate widespread contamination events. Of course, the environmental concentrations of these toxins are expected to be extremely low, therefore highly sensitive and accurate methods are required for their determination. Since ionization of non-polar compounds through electrospray and APCI is difficult and inefficient, we evaluate the performance of a novel low-flow Atmospheric Pressure Photoionization (APPI) source for the trace detection of various dioxins and furans using rapid Mass Spectrometry workflows. Air, soil and biota (vegetable matter) samples were collected monthly during one year from various locations within the vicinity of an industrial incinerator in Spain. Analytes were extracted and concentrated using soxhlet extraction in toluene and concentrated by rotavapor and nitrogen flow. Various ionization methods as electrospray (ES) and atmospheric pressure chemical ionization (APCI) were evaluated, however, only the low-flow APPI source was capable of providing the necessary performance, in terms of sensitivity, required for detecting all targeted analytes. In total, 10 analytes including 2,3,7,8-tetrachlorodibenzodioxin (TCDD) were detected and characterized using the APPI-MS method. Both PCDDs and PCFDs were detected most efficiently in negative ionization mode. The most abundant ion always corresponded to the loss of a chlorine and addition of an oxygen, yielding [M-Cl+O]- ions. MRM methods were created in order to provide selectivity for each analyte. No chromatographic separation was employed; however, matrix effects were determined to have a negligible impact on analyte signals. Triple Quadrupole Mass Spectrometry was chosen because of its unique potential for high sensitivity and selectivity. The mass spectrometer used was a Sciex´s Qtrap3200 working in negative Multi Reacting Monitoring Mode (MRM). Typically mass detection limits were determined to be near the 1-pg level. The APPI-MS2 technology applied to the detection of PCDD/Fs allows fast and reliable atmospheric analysis, minimizing considerably operational times and costs, with respect other technologies available. In addition, the limit of detection can be easily improved using a more sensitive mass spectrometer since the background in the analysis channel is very low. The APPI developed by SEADM allows polar and non-polar compounds ionization with high efficiency and repeatability.

Keywords: atmospheric pressure photoionization-mass spectrometry (APPI-MS), dioxin, furan, incinerator

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Authors: Samir Ranjbar, Nasrullah Istanekzai

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According to a report published in The Guardian, Kabul, the capital city of Afghanistan is the fifth fastest growing city in the world, whose population has increased fourfold since 2001 from 1.2 million to 4.8 million people. The main reason for this increment is identified as the return of Afghans migrated during the civil war. In addition to the return of immigrants, a steep economic growth due to foreign assistance in last decade creating lots of job opportunities in Kabul resulted in the attraction of individuals from the neighboring provinces as well. However, the development of urban facilities such as water supply system, housing transportation and waste management systems has yet to catch up with this rapid increase in population. Since Kabul city has developed traditionally and municipal governance had very limited capacity to implement municipal bylaws. As an unwanted consequence of this growth 70% of Kabul citizens contributed to developing informal settlement for which we can say that around three million people living in informally settled areas, lacking the very vital social and physical infrastructures of livelihood. This research focuses on a region with 30 ha area and 2100 people residents in the center of Kabul city. A comprehensive land readjustment concept plan has been formulated for this area. Through this concept plan, physical and social infrastructure has been demonstrated and analyzed. Findings of this paper propose a solution for the problems of this unplanned area in Kabul which is readjusting of unplanned area by a self-supporting process. This process does not need governmental budget and can be applied by government, private sectors and landowner associations. Furthermore, by implementing the Land Readjustment process, conceptual plans can be built for unplanned areas, maximum facilities can be brought to the residents’ urban life, improve the environment for the users’ benefit, promote the culture and sense of cooperation, participation and coexistence in the mind of people, improving the transport system, improvement in economic status (the value of land increases due to infrastructure availability and land legalization). In addition to all these benefits for the public, we can raise the revenue of government by collecting the taxes from landowners. This process is implemented in most of countries of the world, it was implemented for the first time in Germany and after that in most cities of Japan as well, and is known as one of the effective processes for infrastructural development. To sum up, the notable characteristic of the Land readjustment process is that it works on the concept of mutual interest in which both landowners and the government take advantage. However, in this process, the engagement of community is very important and without public cooperation, this process can face the failure.

Keywords: land readjustment, informal settlement, Kabul, Afghanistan

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Authors: M. A. C. S. Sampath Fernando, James M. Curran, Renate Meyer

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Model assessment, in the Bayesian context, involves evaluation of the goodness-of-fit and the comparison of several alternative candidate models for predictive accuracy and improvements. In posterior predictive checks, the data simulated under the fitted model is compared with the actual data. Predictive model accuracy is estimated using information criteria such as the Akaike information criterion (AIC), the Bayesian information criterion (BIC), the Deviance information criterion (DIC), and the Watanabe-Akaike information criterion (WAIC). The goal of an information criterion is to obtain an unbiased measure of out-of-sample prediction error. Since posterior checks use the data twice; once for model estimation and once for testing, a bias correction which penalises the model complexity is incorporated in these criteria. Cross-validation (CV) is another method used for examining out-of-sample prediction accuracy. Leave-one-out cross-validation (LOO-CV) is the most computationally expensive variant among the other CV methods, as it fits as many models as the number of observations. Importance sampling (IS), truncated importance sampling (TIS) and Pareto-smoothed importance sampling (PSIS) are generally used as approximations to the exact LOO-CV and utilise the existing MCMC results avoiding expensive computational issues. The reciprocals of the predictive densities calculated over posterior draws for each observation are treated as the raw importance weights. These are in turn used to calculate the approximate LOO-CV of the observation as a weighted average of posterior densities. In IS-LOO, the raw weights are directly used. In contrast, the larger weights are replaced by their modified truncated weights in calculating TIS-LOO and PSIS-LOO. Although, information criteria and LOO-CV are unable to reflect the goodness-of-fit in absolute sense, the differences can be used to measure the relative performance of the models of interest. However, the use of these measures is only valid under specific circumstances. This study has developed 11 models using normal, log-normal, gamma, and student’s t distributions to improve the PCR stutter prediction with forensic data. These models are comprised of four with profile-wide variances, four with locus specific variances, and three which are two-component mixture models. The mean stutter ratio in each model is modeled as a locus specific simple linear regression against a feature of the alleles under study known as the longest uninterrupted sequence (LUS). The use of AIC, BIC, DIC, and WAIC in model comparison has some practical limitations. Even though, IS-LOO, TIS-LOO, and PSIS-LOO are considered to be approximations of the exact LOO-CV, the study observed some drastic deviations in the results. However, there are some interesting relationships among the logarithms of pointwise predictive densities (lppd) calculated under WAIC and the LOO approximation methods. The estimated overall lppd is a relative measure that reflects the overall goodness-of-fit of the model. Parallel log-likelihood profiles for the models conditional on equal posterior variances in lppds were observed. This study illustrates the limitations of the information criteria in practical model comparison problems. In addition, the relationships among LOO-CV approximation methods and WAIC with their limitations are discussed. Finally, useful recommendations that may help in practical model comparisons with these methods are provided.

Keywords: cross-validation, importance sampling, information criteria, predictive accuracy

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Authors: Scott Wysong

Abstract:

Qatar will spend billions of dollars to host the 2022 World Cup. While football fans around the globe get excited to cheer on their favorite team every four years, critics debate the merits of a country hosting such an expensive and large-scale event. That is, the host countries spend billions of dollars on stadiums and infrastructure to attract these mega sporting events with the hope of equitable returns in economic impact and creating jobs. Yet, in many cases, the host countries are left in debt with decaying venues. There are benefits beyond the economic impact of hosting mega-events. For example, citizens are often proud of their city/country to host these famous events. Yet, often overlooked in the literature is the proposition that serving as the host for a mega-event may enhance the country’s brand image, not only as a tourist destination but for the products made in that country of origin. This research aims to explore this phenomenon by taking an exploratory look at consumer perceptions of three host countries of a mega-event in sports. In 2014, the U.S., Chinese and Finn (Finland) consumer attitudes toward Brazil and its products were measured before and after the World Cup via surveys (n=89). An Analysis of Variance (ANOVA) revealed that there were no statistically significant differences in the pre-and post-World Cup perceptions of Brazil’s brand personality or country-of-origin image. After the World Cup in 2018, qualitative interviews were held with U.S. sports fans (n=17) in an effort to further explore consumer perceptions of products made in the host country: Russia. A consistent theme of distrust and corruption with Russian products emerged despite their hosting of this prestigious global event. In late 2021, U.S. football (soccer) fans (n=42) and non-fans (n=37) were surveyed about the upcoming 2022 World Cup. A regression analysis revealed that how much an individual indicated that they were a soccer fan did not significantly influence their desire to visit Qatar or try products from Qatar in the future even though the country was hosting the World Cup—in the end, hosting a mega-event as grand as the World Cup showcases the country to the world. However, it seems to have little impact on consumer perceptions of the country, as a whole, or its brands. That is, the World Cup appeared to enhance already pre-existing stereotypes about Brazil (e.g., beaches, partying and fun, yet with crime and poverty), Russia (e.g., cold weather, vodka and business corruption) and Qatar (desert and oil). Moreover, across all three countries, respondents could rarely name a brand from the host country. Because mega-events cost a lot of time and money, countries need to do more to market their country and its brands when hosting. In addition, these countries would be wise to measure the impact of the event from different perspectives. Hence, we put forth a comprehensive future research agenda to further the understanding of how countries, and their brands, can benefit from hosting a mega sporting event.

Keywords: branding, country-of-origin effects, mega sporting events, return on investment

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Authors: Anand R. Nair, Markus Trenker

Abstract:

Lifting body concepts were conceived as early as 1917 and patented by Roy Scroggs. It was an idea of using the fuselage as a lift producing body with no or small wings. Many of these designs were developed and even flight tested between 1920’s to 1970’s, but it was not pursued further for commercial flight as at lower airspeeds, such a configuration was incapable to produce sufficient lift for the entire aircraft. The concept presented in this contribution is combining the lifting body design along with a fixed wing to maximise the lift produced by the aircraft. Conventional aircraft fuselages are designed to be aerodynamically efficient, which is to minimise the drag; however, these fuselages produce very minimal or negligible lift. For the design of an unmanned fixed wing transport aircraft, many of the restrictions which are present for commercial aircraft in terms of fuselage design can be excluded, such as windows for the passengers/pilots, cabin-environment systems, emergency exits, and pressurization systems. This gives new flexibility to design fuselages which are unconventionally shaped to contribute to the lift of the aircraft. The two lifting body concepts presented in this contribution are targeting different applications: For a fast cargo delivery drone, the fuselage is based on a scaled airfoil shape with a cargo capacity of 500 kg for euro pallets. The aircraft has a span of 14 m and reaches 1500 km at a cruising speed of 90 m/s. The aircraft could also easily be adapted to accommodate pilot and passengers with modifications to the internal structures, but pressurization is not included as the service ceiling envisioned for this type of aircraft is limited to 10,000 ft. The next concept to be investigated is called a multi-purpose drone, which incorporates a different type of lifting body and is a much more versatile aircraft as it will have a VTOL capability. The aircraft will have a wingspan of approximately 6 m and flight speeds of 60 m/s within the same service ceiling as the fast cargo delivery drone. The multi-purpose drone can be easily adapted for various applications such as firefighting, agricultural purposes, surveillance, and even passenger transport. Lifting body designs are not a new concept, but their effectiveness in terms of cargo transportation has not been widely investigated. Due to their enhanced lift producing capability, lifting body designs enable the reduction of the wing area and the overall weight of the aircraft. This will, in turn, reduce the thrust requirement and ultimately the fuel consumption. The various designs proposed in this contribution will be based on the general aviation category of aircrafts and will be focussed on unmanned methods of operation. These unmanned fixed-wing transport drones will feature appropriate cargo loading/unloading concepts which can accommodate large size cargo for efficient time management and ease of operation. The various designs will be compared in performance to their conventional counterpart to understand their benefits/shortcomings in terms of design, performance, complexity, and ease of operation. The majority of the performance analysis will be carried out using industry relevant standards in computational fluid dynamics software packages.

Keywords: lifting body concept, computational fluid dynamics, unmanned fixed-wing aircraft, cargo drone

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Authors: Ibrahim Rassoul, A. Serir, E-K. Si Ahmed, J. Legrand

Abstract:

The acronym PEM refers to Proton Exchange Membrane or alternatively Polymer Electrolyte Membrane. Due to its high efficiency, low operating temperature (30–80 °C), and rapid evolution over the past decade, PEMFCs are increasingly emerging as a viable alternative clean power source for automobile and stationary applications. Before PEMFCs can be employed to power automobiles and homes, several key technical challenges must be properly addressed. One technical challenge is elucidating the mechanisms underlying water transport in and removal from PEMFCs. On one hand, sufficient water is needed in the polymer electrolyte membrane or PEM to maintain sufficiently high proton conductivity. On the other hand, too much liquid water present in the cathode can cause “flooding” (that is, pore space is filled with excessive liquid water) and hinder the transport of the oxygen reactant from the gas flow channel (GFC) to the three-phase reaction sites. The experimental transparent fuel cell used in this work was designed to represent actual full scale of fuel cell geometry. According to the operating conditions, a number of flow regimes may appear in the microchannel: droplet flow, blockage water liquid bridge /plug (concave and convex forms), slug/plug flow and film flow. Some of flow patterns are new, while others have been already observed in PEMFC microchannels. An algorithm in MATLAB was developed to automatically determine the flow structure (e.g. slug, droplet, plug, and film) of detected liquid water in the test microchannels and yield information pertaining to the distribution of water among the different flow structures. A video processing algorithm was developed to automatically detect dynamic and static liquid water present in the gas channels and generate relevant quantitative information. The potential benefit of this software allows the user to obtain a more precise and systematic way to obtain measurements from images of small objects. The void fractions are also determined based on images analysis. The aim of this work is to provide a comprehensive characterization of two-phase flow in an operating fuel cell which can be used towards the optimization of water management and informs design guidelines for gas delivery microchannels for fuel cells and its essential in the design and control of diverse applications. The approach will combine numerical modeling with experimental visualization and measurements.

Keywords: polymer electrolyte fuel cell, air-water two phase flow, gas diffusion layer, microchannels, advancing contact angle, receding contact angle, void fraction, surface tension, image processing

Procedia PDF Downloads 312

Authors: Martina Grdiša, Filip Varga, Nina Jeran, Ante Turudić, Zlatko Šatović

Abstract:

Dalmatian pyrethrum (Tanacetum cinerariifolium (Trevir.) Sch. Bip.) is a plant species that occurs naturally in the eastern Mediterranean. It is of immense economic importance as it synthesizes and accumulates the phytochemical compound pyrethrin. Pyrethrin consists of several monoterpene esters (pyrethrin I and II, cinerin I and II and jasmolin I and II), which have insecticidal and repellent activity through their synergistic action. In this study, 15 natural Dalmatian pyrethrum populations were sampled along their natural range in Croatia, Bosnia and Herzegovina and Montenegro to characterize and compare their pyrethrin profiles and to define the bioclimatic factors associated with the accumulation of each pyrethrin compound. Pyrethrins were extracted from the dried flower heads of Dalmatian pyrethrum using ultrasound-assisted extraction and the amount of each compound was quantified using high-performance liquid chromatography coupled to DAD-UV /VIS. The biochemical data were subjected to analysis of variance, correlation analysis and multivariate analysis. Quantitative variability within and among populations was found, with population P15 Vranjske Njive, Podgorica having the significantly highest pyrethrin I content (66.47% of total pyrethrin content), while the highest levels of total pyrethrin were found in P14 Budva (1.27% of dry flower weight; DW), followed by P08 Korčula (1.15% DW). Based on the environmental conditions at the sampling sites of the populations, five bioclimatic groups were distinguished, referred to as A, B, C, D, and E, each with rare chemical profile. The first group (A) consisted of the northern Adriatic population P01 Vrbnik, Krk and the population P06 Sevid - the coastal population of the central Adriatic, and generally differed significantly from the other bioclimatic groups by higher average jasmolin II values (2.13% of total pyrethrin). The second group (B) consisted of two central Adriatic island populations (P02 Telašćica, Dugi otok and P03 Žman, Dugi otok), while the remaining central Adriatic island populations were grouped in bioclimatic group C, which was characterized by the significantly highest average pyrethrin II (48.52% of total pyrethrin) and cinerin II (5.31% DW) content. The South Adriatic inland populations P10 Srđ and P11 Trebinje (Bosnia and Herzegovina), and the populations from Montenegro (P12 Grahovo, P13 Lovćen, P14 Budva and P15 Vranjske Njive, Podgorica) formed bioclimatic group E. This bioclimatic group was characterized by the highest average values for pyrethrin I (53.07 % of total pyrethrin), total pyrethrin content (1.06 % DW) and the ratio of pyrethrin I and II (1.85). Slightly lower values (although not significant) for the latter traits were detected in bioclimatic group D (southern Adriatic island populations P07 Vis, P08 Korčula and P09 Mljet). A weak but significant correlation was found between the levels of some pyrethrin compounds and bioclimatic variables (e.g., BIO03 Isothermality and BIO04 Temperature Seasonality), which explains part of the variability observed in the populations studied. This suggests the interconnection between bioclimatic variables and biochemical profiles either through the selection of adapted genotypes or through the ability of species to alter the expression of biochemical traits in response to environmental changes.

Keywords: biopesticides, biochemical variability, pyrethrin, Tanacetum cinerariifolium

Procedia PDF Downloads 155